Secure networked inference with unreliable data sources

Aditya Vempaty, Bhavya Kailkhura, Pramod K. Varshney

Research output: Book/ReportBook

Abstract

The book presents theory and algorithms for secure networked inference in the presence of Byzantines. It derives fundamental limits of networked inference in the presence of Byzantine data and designs robust strategies to ensure reliable performance for several practical network architectures. In particular, it addresses inference (or learning) processes such as detection, estimation or classification, and parallel, hierarchical, and fully decentralized (peer-to-peer) system architectures. Furthermore, it discusses a number of new directions and heuristics to tackle the problem of design complexity in these practical network architectures for inference.

Original languageEnglish (US)
PublisherSpringer Singapore
Number of pages208
ISBN (Electronic)9789811323126
ISBN (Print)9789811323119
DOIs
StatePublished - Jan 1 2018

Keywords

  • Byzantines
  • Data falsification
  • Data fusion
  • Distributed detection
  • Distributed estimation
  • Distributed inference
  • Distributed learning
  • Network security information fusion
  • Wireless networks
  • Wireless sensor networks

ASJC Scopus subject areas

  • Computer Science(all)
  • Engineering(all)

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